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Journal articles on the topic 'Cryospheric mapping'
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1
Brenning, A., M. A. Peña, S. Long, and A. Soliman. "Thermal remote sensing of ice-debris landforms using ASTER: an example from the Chilean Andes." Cryosphere 6, no. 2 (March 30, 2012): 367–82. http://dx.doi.org/10.5194/tc-6-367-2012.
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Abstract. Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditions or mapping rock glaciers and debris-covered glaciers. We explore the potential of thermal imaging and in particular thermal inertia mapping in mountain cryospheric research, focusing on the relationships between ground surface temperatures and the presence of ice-debris landforms on one side and land surface temperature (LST) and apparent thermal inertia (ATI) on the other. In our case study we utilize ASTER daytime and nighttime imagery and in-situ measurements of near-surface ground temperature (NSGT) in the Mediterranean Andes during a snow-free and dry observation period in late summer. Spatial patterns of LST and NSGT were mostly consistent with each other both at daytime and at nighttime. Daytime LST over ice-debris landforms was decreased and ATI consequently increased compared to other debris surfaces under otherwise equal conditions, but NSGT showed contradictory results, which underlines the complexity and possible scale dependence of ATI in heterogeneous substrates with the presence of a thermal mismatch and a heat sink at depth. While our results demonstrate the utility of thermal imaging and ATI mapping in a mountain cryospheric context, further research is needed for a better interpretation of ATI patterns in complex thermophysical conditions.
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Brenning, A., M. A. Peña, S. Long, and A. Soliman. "Thermal remote sensing of ice-debris landforms using ASTER." Cryosphere Discussions 5, no. 5 (October 24, 2011): 2895–933. http://dx.doi.org/10.5194/tcd-5-2895-2011.
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Abstract. Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditions or mapping rock glaciers and debris-covered glaciers. We explore the potentials of thermal imaging and in particular thermal inertia mapping in mountain cryospheric research, focusing on the relationships between ground surface temperatures and the presence of ice-debris landforms on one side and land surface temperature (LST) and apparent thermal inertia (ATI) on the other. In our case study we utilize ASTER daytime and nighttime imagery and in-situ measurements of near-surface ground temperature (NSGT) in the Mediterranean Andes during a snow-free and dry observation period in late summer. Spatial patterns of LST and NSGT were mostly consistent with each other both at daytime and at nighttime. Daytime LST over ice-debris landforms was decreased and ATI consequently increased compared to other debris surfaces under otherwise equal conditions, but NSGT showed contradictory results, which underlines the complexity and possible scale dependence of ATI in heterogeneous substrates with the presence of a thermal mismatch and a heat sink at depth. While our results demonstrate the utility of thermal imaging and ATI mapping in a mountain cryospheric context, further research is needed for a better interpretation of ATI patterns in complex thermophysical conditions
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Monserrat, O., C. Cardenas, P. Olea, V. Krishnakumar, and B. Crippa. "POTENTIALITIES OF SENTINEL-1 FOR MAPPING AND MONITORING GEOLOGICAL AND CRYOSPHERIC PROCESSES IN THE PATAGONIA REGION (CHILE)." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-3/W2-2020 (October 29, 2020): 137–42. http://dx.doi.org/10.5194/isprs-annals-iv-3-w2-2020-137-2020.
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Abstract. This work shows two examples on the use of Sentinel-1 data for monitoring different natural processes, like active geohazards or glacier dynamics in the Patagonia region. Sentinel-1 is a two-satellite constellation, launched by the European Space Agency (ESA), that provides SAR imagery with interferometric capabilities. It is in operation since 2014 and has supposed a significant improvement in the exploitation of these type of data for applications like natural hazards mapping and monitoring. The acquisition policy, that guarantees an acquisition each few days (12 days in Patagonia region) for both ascending and descending trajectories, and the data distribution policy, that allows free access to the images without legal constrains, are the main reasons for this improvement. These two aspects allowed not only to assure the data in the past but also to perform monitoring plans at medium-long term. In this work we show the potentialities of the use of these data in the Patagonia region through the application of two different techniques in two different application test sites: urban areas and glaciers.
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Jawak, Shridhar D., Alvarinho J. Luis, Peter T. Fretwell, Peter Convey, and Udhayaraj A. Durairajan. "Semiautomated Detection and Mapping of Vegetation Distribution in the Antarctic Environment Using Spatial-Spectral Characteristics of WorldView-2 Imagery." Remote Sensing 11, no. 16 (August 15, 2019): 1909. http://dx.doi.org/10.3390/rs11161909.
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Effective monitoring of changes in the geographic distribution of cryospheric vegetation requires high-resolution and accurate baseline maps. The rationale of the present study is to compare multiple feature extraction approaches to remotely mapping vegetation in Antarctica, assessing which give the greatest accuracy and reproducibility relative to those currently available. This study provides precise, high-resolution, and refined baseline information on vegetation distribution as is required to enable future spatiotemporal change analyses of the vegetation in Antarctica. We designed and implemented a semiautomated customized normalized difference vegetation index (NDVI) approach for extracting cryospheric vegetation by incorporating very high resolution (VHR) 8-band WorldView-2 (WV-2) satellite data. The viability of state-of-the-art target detection, spectral processing/matching, and pixel-wise supervised classification feature extraction techniques are compared with the customized NDVI approach devised in this study. An extensive quantitative and comparative assessment was made by evaluating four semiautomatic feature extraction approaches consisting of 16 feature extraction standalone methods (four customized NDVI plus 12 existing methods) for mapping vegetation on Fisher Island and Stornes Peninsula in the Larsemann Hills, situated on continental east Antarctica. The results indicated that the customized NDVI approach achieved superior performance (average bias error ranged from ~6.44 ± 1.34% to ~11.55 ± 1.34%) and highest statistical stability in terms of performance when compared with existing feature extraction approaches. Overall, the accuracy analysis of the vegetation mapping relative to manually digitized reference data (supplemented by validation with ground truthing) indicated that the 16 semi-automatic mapping methods representing four general feature extraction approaches extracted vegetated area from Fisher Island and Stornes Peninsula totalling between 2.38 and 3.72 km2 (2.85 ± 0.10 km2 on average) with bias values ranging from 3.49 to 31.39% (average 12.81 ± 1.88%) and average root mean square error (RMSE) of 0.41 km2 (14.73 ± 1.88%). Further, the robustness of the analyses and results were endorsed by a cross-validation experiment conducted to map vegetation from the Schirmacher Oasis, East Antarctica. Based on the robust comparative analysis of these 16 methods, vegetation maps of the Larsemann Hills and Schirmacher Oasis were derived by ensemble merging of the five top-performing methods (Mixture Tuned Matched Filtering, Matched Filtering, Matched Filtering/Spectral Angle Mapper Ratio, NDVI-2, and NDVI-4). This study is the first of its kind to detect and map sparse and isolated vegetated patches (with smallest area of 0.25 m2) in East Antarctica using VHR data and to use ensemble merging of feature extraction methods, and provides access to an important indicator for environmental change.
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Nolan, M., C. F. Larsen, and M. Sturm. "Mapping snow-depth from manned-aircraft on landscape scales at centimeter resolution using Structure-from-Motion photogrammetry." Cryosphere Discussions 9, no. 1 (January 15, 2015): 333–81. http://dx.doi.org/10.5194/tcd-9-333-2015.
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Abstract. Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers-to-entry and now allow repeat-mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these techniques to the measurement of snow depth from manned aircraft. The main airborne hardware consists of a consumer-grade digital camera coupled to a dual-frequency GPS. The photogrammetric processing is done using a commercially-available implementation of the Structure from Motion (SfM) algorithm. The system hardware and software, exclusive of aircraft, costs less than USD 30 000. The technique creates directly-georeferenced maps without ground control, further reducing costs. To map snow depth, we made digital elevation models (DEMs) during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs). We assessed the accuracy (geolocation) and precision (repeatability) of our DEMs through comparisons to ground control points and to time-series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by another photogrammetric system. We empirically determined an accuracy of ± 30 cm and a precision of ± 8 cm (both 95% confidence) for our methods. We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and these depth distributions were statistically identical at 95% confidence. Due to the precision of this technique, other real changes on the ground such as frost heave, vegetative compaction by snow, and even footprints become sources of error in the measurement of thin snow packs (< 20 cm). The ability to directly measure such small changes over entire landscapes eliminates the need to extrapolate isolated field measurements. The fact that this mapping can be done at substantially lower costs than current methods may transform the way we approach studying change in the cryosphere.
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Mazhar, Nausheen, Dania Amjad, Kanwal Javid, Rumana Siddiqui, Muhammad Ameer Nawaz, and Zaynah Sohail Butt. "Mapping Fluctuations of Hispar Glacier, Karakoram, using Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDSPCSI)." International Journal of Economic and Environmental Geology 11, no. 4 (March 11, 2021): 48–55. http://dx.doi.org/10.46660/ijeeg.vol11.iss4.2020.516.
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Investigation of the fluctuations in the snow-covered area of the major glaciers of the Karakoram range is essential for proper water resource management in Pakistan, since its glaciers are responding differently to the rising temperatures. The objective of this paper is to map snow covered area of Hispar glacier in Hunza river basin for the years 1990, 2010 and 2018. Two techniques, (NDPCSI) Normalized Difference Principal Component Snow Index and (NDSI) Normalized Difference Snow Index were used. Hispar glacier of the Hunza basin has lost 114 km2 of its ice cover area, during the last 28 years, with an alarming annual retreat rate of 1.67 km2 of glacier ice from 1990 to 2018. Hunza basin experienced a +1°C rise in both mean minimum and mean maximum temperature during 2007 to 2018.as a result, Karakorum ice reserves have been affected by rising temperature of the region. Due to temperature rise, retreat of snowcovered area of Hispar, Karakoram mountain range shows a shift in the cryospheric hazard zone.
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Jawak, Shridhar D., Sagar F. Wankhede, and Alvarinho J. Luis. "Explorative Study on Mapping Surface Facies of Selected Glaciers from Chandra Basin, Himalaya Using WorldView-2 Data." Remote Sensing 11, no. 10 (May 21, 2019): 1207. http://dx.doi.org/10.3390/rs11101207.
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Mapping of surface glacier facies has been a part of several glaciological applications. The study of glacier facies in the Himalayas has gained momentum in the last decade owing to the implications imposed by these facies on the melt characteristics of the glaciers. Some of the most commonly reported surface facies in the Himalayas are snow, ice, ice mixed debris, and debris. The precision of the techniques used to extract glacier facies is of high importance, as the result of many cryospheric studies and economic reforms rely on it. An assessment of a customized semi-automated protocol against conventional and advanced mapping algorithms for mapping glacier surface facies is presented in this study. Customized spectral index ratios (SIRs) are developed for effective extraction of surface facies using thresholding in an object-based environment. This method was then tested on conventional and advanced classification algorithms for an evaluation of the mapping accuracy for five glaciers located in the Himalayas, using very high-resolution WorldView-2 imagery. The results indicate that the object-based image analysis (OBIA) based semi-automated SIR approach achieved a higher average overall accuracy of 87.33% (κ = 0.85) than the pixel-based image analysis (PBIA) approach. Among the conventional methods, the Maximum Likelihood performed the best, with an overall accuracy of 78.71% (κ = 0.75). The Constrained Energy Minimization, with an overall accuracy of 68.76% (κ = 0.63), was the best performer of the advanced algorithms. The advanced methods greatly underperformed in this study. The proposed SIRs show a promise in the mapping of minor features such as crevasses and in the discrimination between ice-mixed debris and debris. We have efficiently mapped surface glacier facies independently of short-wave infrared bands (SWIR). There is a scope for the transferability of the proposed SIRs and their performance in varying scenarios.
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Nolan, M., C. Larsen, and M. Sturm. "Mapping snow depth from manned aircraft on landscape scales at centimeter resolution using structure-from-motion photogrammetry." Cryosphere 9, no. 4 (August 5, 2015): 1445–63. http://dx.doi.org/10.5194/tc-9-1445-2015.
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Abstract. Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers to entry and now allow repeat mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these advancements to the measurement of snow depth from manned aircraft. Our main airborne hardware consists of a consumer-grade digital camera directly coupled to a dual-frequency GPS; no inertial motion unit (IMU) or on-board computer is required, such that system hardware and software costs less than USD 30 000, exclusive of aircraft. The photogrammetric processing is done using a commercially available implementation of the structure from motion (SfM) algorithm. The system is simple enough that it can be operated by the pilot without additional assistance and the technique creates directly georeferenced maps without ground control, further reducing overall costs. To map snow depth, we made digital elevation models (DEMs) during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs). We assessed the accuracy (real-world geolocation) and precision (repeatability) of our DEMs through comparisons to ground control points and to time series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by a similar photogrammetric system. We empirically determined that our DEMs have a geolocation accuracy of ±30 cm and a repeatability of ±8 cm (both 95 % confidence). We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 separate test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and were statistically identical at 95 % confidence. Due to the precision of this technique, other real changes on the ground such as frost heave, vegetative compaction by snow, and even footprints become sources of error in the measurement of thin snow packs (< 20 cm). The ability to directly measure such small changes over entire landscapes eliminates the need to extrapolate limited field measurements. The fact that this mapping can be done at substantially lower costs than current methods may transform the way we approach studying change in the cryosphere.
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Fraser, R. H., I. Olthof, M. Maloley, R. Fernandes, C. Prevost, and J. van der Sluijs. "UAV PHOTOGRAMMETRY FOR MAPPING AND MONITORING OF NORTHERN PERMAFROST LANDSCAPES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 27, 2015): 361. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-361-2015.
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Northern environments are changing in response to recent climate warming, resource development, and natural disturbances. The Arctic climate has warmed by 2–3°C since the 1950’s, causing a range of cryospheric changes including declines in sea ice extent, snow cover duration, and glacier mass, and warming permafrost. The terrestrial Arctic has also undergone significant temperature-driven changes in the form of increased thermokarst, larger tundra fires, and enhanced shrub growth. Monitoring these changes to inform land managers and decision makers is challenging due to the vast spatial extents involved and difficult access. <br><br> Environmental monitoring in Canada’s North is often based on local-scale measurements derived from aerial reconnaissance and photography, and ecological, hydrologic, and geologic sampling and surveying. Satellite remote sensing can provide a complementary tool for more spatially comprehensive monitoring but at coarser spatial resolutions. Satellite remote sensing has been used to map Arctic landscape changes related to vegetation productivity, lake expansion and drainage, glacier retreat, thermokarst, and wildfire activity. However, a current limitation with existing satellite-based techniques is the measurement gap between field measurements and high resolution satellite imagery. Bridging this gap is important for scaling up field measurements to landscape levels, and validating and calibrating satellite-based analyses. This gap can be filled to a certain extent using helicopter or fixed-wing aerial surveys, but at a cost that is often prohibitive. <br><br> Unmanned aerial vehicle (UAV) technology has only recently progressed to the point where it can provide an inexpensive and efficient means of capturing imagery at this middle scale of measurement with detail that is adequate to interpret Arctic vegetation (i.e. 1–5 cm) and coverage that can be directly related to satellite imagery (1–10 km<sup>2</sup>). Unlike satellite measurements, UAVs permit frequent surveys (e.g. for monitoring vegetation phenology, fires, and hydrology), are not constrained by repeat cycle or cloud cover, can be rapidly deployed following a significant event, and are better suited than manned aircraft for mapping small areas. UAVs are becoming more common for agriculture, law enforcement, and marketing, but their use in the Arctic is still rare and represents untapped technology for northern mapping, monitoring, and environmental research. <br><br> We are conducting surveys over a range of sensitive or changing northern landscapes using a variety of UAV multicopter platforms and small sensors. Survey targets include retrogressive thaw slumps, tundra shrub vegetation, recently burned vegetation, road infrastructure, and snow. Working with scientific partners involved in northern monitoring programs (NWT CIMP, CHARS, NASA ABOVE, NRCan-GSC) we are investigating the advantages, challenges, and best practices for acquiring high resolution imagery from multicopters to create detailed orthomosaics and co-registered 3D terrain models. Colour and multispectral orthomosaics are being integrated with field measurements and satellite imagery to conduct spatial scaling of environmental parameters. Highly detailed digital terrain models derived using structure from motion (SfM) photogrammetry are being applied to measure thaw slump morphology and change, snow depth, tundra vegetation structure, and surface condition of road infrastructure. <br><br> These surveys and monitoring applications demonstrate that UAV-based photogrammetry is poised to make a rapid contribution to a wide range of northern monitoring and research applications.
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Romanov, Peter. "Global Multisensor Automated satellite-based Snow and Ice Mapping System (GMASI) for cryosphere monitoring." Remote Sensing of Environment 196 (July 2017): 42–55. http://dx.doi.org/10.1016/j.rse.2017.04.023.
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Ødegård, Rune S., and Rune Solberg. "Technological concepts for modelling, monitoring and mapping the terrestrial cryosphere on continental to global scale." Norsk Geografisk Tidsskrift - Norwegian Journal of Geography 56, no. 2 (January 2002): 174–78. http://dx.doi.org/10.1080/002919502760056503.
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Leigh, J. R., C. R. Stokes, R. J. Carr, I. S. Evans, L. M. Andreassen, and D. J. A. Evans. "Identifying and mapping very small (<0.5 km2) mountain glaciers on coarse to high-resolution imagery." Journal of Glaciology 65, no. 254 (September 27, 2019): 873–88. http://dx.doi.org/10.1017/jog.2019.50.
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AbstractSmall mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be <0.5 km2) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01–0.05 km2). Here, we compare the ability of different remote-sensing approaches to identify and map very small glaciers on imagery of varying spatial resolutions (30–0.25 m) and investigate how operator subjectivity influences the results. Based on this analysis, we support the use of a minimum size-threshold of 0.01 km2 for imagery with coarse to medium spatial resolution (30–10 m). However, when mapping on high-resolution imagery (<1 m) with minimal seasonal snow cover, glaciers <0.05 km2 and even <0.01 km2 are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we develop a set of criteria to enable the identification of very small glaciers and classify them as certain, probable or possible. This should facilitate a more consistent approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.
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Ray, R. D., and E. D. Zaron. "M2 Internal Tides and Their Observed Wavenumber Spectra from Satellite Altimetry." Journal of Physical Oceanography 46, no. 1 (January 2016): 3–22. http://dx.doi.org/10.1175/jpo-d-15-0065.1.
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AbstractA near-global chart of surface elevations associated with the stationary M2 internal tide is empirically constructed from multimission satellite altimeter data. An advantage of a strictly empirical mapping approach is that results are independent of assumptions about ocean wave dynamics and, in fact, can be used to test such assumptions. A disadvantage is that present-day altimeter coverage is only marginally adequate to support mapping such short-wavelength features. Moreover, predominantly north–south ground-track orientations and contamination from nontidal oceanographic variability can lead to deficiencies in mapped tides. Independent data from Cryosphere Satellite-2 (CryoSat-2) and other altimeters are used to test the solutions and show positive reduction in variance except in regions of large mesoscale variability. The tidal fields are subjected to two-dimensional wavenumber spectral analysis, which allows for the construction of an empirical map of modal wavelengths. Mode-1 wavelengths show good agreement with theoretical wavelengths calculated from the ocean’s mean stratification, with a few localized exceptions (e.g., Tasman Sea). Mode-2 waves are detectable in much of the ocean, with wavelengths in reasonable agreement with theoretical expectations, but their spectral signatures grow too weak to map in some regions.
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Vosselman, G., S. J. Oude Elberink, and M. Y. Yang. "PREFACE – ISPRS GEOSPATIAL WEEK 2019." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 1. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1-2019.
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<p><strong>Abstract.</strong> The ISPRS Geospatial Week 2019 is a combination of 13 workshops organised by 30 ISPRS Working Groups active in areas of interest of ISPRS. The Geospatial Week 2019 is held from 10–14 June 2019, and is convened by the University of Twente acting as local organiser. The Geospatial Week 2019 is the fourth edition, after Antalya Turkey in 2013, La Grande Motte France in 2015 and Wuhan China in 2017.</p><p>The following 13 workshops provide excellent opportunities to discuss the latest developments in the fields of sensors, photogrammetry, remote sensing, and spatial information sciences:</p> <ul> <li>C3M&amp;GBD – Collaborative Crowdsourced Cloud Mapping and Geospatial Big Data</li> <li>CHGCS – Cryosphere and Hydrosphere for Global Change Studies</li> <li>EuroCow-M3DMaN – Joint European Calibration and Orientation Workshop and Workshop onMulti-sensor systems for 3D Mapping and Navigation</li> <li>HyperMLPA – Hyperspectral Sensing meets Machine Learning and Pattern Analysis</li> <li>Indoor3D</li> <li>ISSDQ – International Symposium on Spatial Data Quality</li> <li>IWIDF – International Workshop on Image and Data Fusion</li> <li>Laser Scanning</li> <li>PRSM – Planetary Remote Sensing and Mapping</li> <li>SarCon – Advances in SAR: Constellations, Signal processing, and Applications</li> <li>Semantics3D – Semantic Scene Analysis and 3D Reconstruction from Images and ImageSequences</li> <li>SmartGeoApps – Advanced Geospatial Applications for Smart Cities and Regions</li> <li>UAV-g – Unmanned Aerial Vehicles in Geomatics</li> </ul> <p>Many of the workshops are part of well-established series of workshops convened in the past. They cover topics like UAV photogrammetry, laser scanning, spatial data quality, scene understanding, hyperspectral imaging, and crowd sourcing and collaborative mapping with applications ranging from indoor mapping and smart cities to global cryosphere and hydrosphere studies and planetary mapping.</p><p>In total 143 full papers and 357 extended abstracts were submitted by authors from 63 countries. 1250 reviews have been delivered by 295 reviewers. A total of 81 full papers have been accepted for the volume IV-2/W5 of the International Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Another 289 papers are published in volume XLII-2/W13 of the International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences.</p><p>The editors would like to thank all contributing authors, reviewers and all workshop organizers for their role in preparing and organizing the Geospatial Week 2019. Thanks to their contributions, we can offer an excessive and varying collection in the Annals and the Archives.</p><p>We hope you enjoy reading the proceedings.</p><p>George Vosselman, Geospatial Week Director 2019, General Chair<br> Sander Oude Elberink, Programme Chair<br> Michael Ying Yang, Programme Chair</p>
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Vosselman, G., S. J. Oude Elberink, and M. Y. Yang. "PREFACE – ISPRS Geospatial Week 2019." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 1. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-1-2019.
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<p><strong>Abstract.</strong> The ISPRS Geospatial Week 2019 is a combination of 13 workshops organised by 30 ISPRS Working Groups active in areas of interest of ISPRS. The Geospatial Week 2019 is held from 10–14 June 2019, and is convened by the University of Twente acting as local organiser. The Geospatial Week 2019 is the fourth edition, after Antalya Turkey in 2013, La Grande Motte France in 2015 and Wuhan China in 2017.</p><p>The following 13 workshops provide excellent opportunities to discuss the latest developments in the fields of sensors, photogrammetry, remote sensing, and spatial information sciences:</p> <ul> <li>C3M&amp;GBD – Collaborative Crowdsourced Cloud Mapping and Geospatial Big Data</li> <li>CHGCS – Cryosphere and Hydrosphere for Global Change Studies</li> <li>EuroCow-M3DMaN – Joint European Calibration and Orientation Workshop and Workshop onMulti-sensor systems for 3D Mapping and Navigation</li> <li>HyperMLPA – Hyperspectral Sensing meets Machine Learning and Pattern Analysis</li> <li>Indoor3D</li> <li>ISSDQ – International Symposium on Spatial Data Quality</li> <li>IWIDF – International Workshop on Image and Data Fusion</li> <li>Laser Scanning</li> <li>PRSM – Planetary Remote Sensing and Mapping</li> <li>SarCon – Advances in SAR: Constellations, Signal processing, and Applications</li> <li>Semantics3D – Semantic Scene Analysis and 3D Reconstruction from Images and ImageSequences</li> <li>SmartGeoApps – Advanced Geospatial Applications for Smart Cities and Regions</li> <li>UAV-g – Unmanned Aerial Vehicles in Geomatics</li> </ul> <p>Many of the workshops are part of well-established series of workshops convened in the past. They cover topics like UAV photogrammetry, laser scanning, spatial data quality, scene understanding, hyperspectral imaging, and crowd sourcing and collaborative mapping with applications ranging from indoor mapping and smart cities to global cryosphere and hydrosphere studies and planetary mapping.</p><p>In total 143 full papers and 357 extended abstracts were submitted by authors from 63 countries. 1250 reviews have been delivered by 295 reviewers. A total of 81 full papers have been accepted for the volume IV-2/W5 of the International Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Another 289 papers are published in volume XLII-2/W13 of the International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences.</p><p>The editors would like to thank all contributing authors, reviewers and all workshop organizers for their role in preparing and organizing the Geospatial Week 2019. Thanks to their contributions, we can offer an excessive and varying collection in the Annals and the Archives.</p><p>We hope you enjoy reading the proceedings.</p><p>George Vosselman, Geospatial Week Director 2019, General Chair<br /> Sander Oude Elberink, Programme Chair<br /> Michael Ying Yang, Programme Chair</p>
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Sahu, R., and R. D. Gupta. "CONCEPTUAL FRAMEWORK OF COMBINED PIXEL AND OBJECT-BASED METHOD FOR DELINEATION OF DEBRIS-COVERED GLACIERS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (November 15, 2018): 173–80. http://dx.doi.org/10.5194/isprs-annals-iv-5-173-2018.
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<p><strong>Abstract.</strong> Delineation of the glacier is an important task for understanding response of glaciers to climate. In Himalayan region, most of the glaciers are covered with debris. Supraglacial debris works as an obstacle for automatic mapping of glacier using remote sensing data. Different methods have been used to reduce this difficulty based on pixel-based and object-based approaches using optical data, thermal data and DEM. Pixel-based glacier mapping is a traditional method for delineation of the glacier but the object-based method has emerged as a new approach in cryosphere application leading to its successful application in different applications. All pixel-based methods require some degree of manual correction because these can’t be delineated automatically, especially in shadow area and debris covered part of the glacier. In the majority of studies, the object-based method has provided higher accuracy to delineate the debris-covered glacier. Spatially high spatial resolution satellite data is best suited for object-based image classification. In future, a combination of pixel-based method and object-based method can be attempted for delineation of the debris-covered glacier along with its critical analysis for suitability. The present paper critically reviews pixel-based and object-based methods as well as provides a framework for combined pixel and object-based method for delineation of debris-covered glacier.</p>
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Dibarboure, G., P. Y. Le Traon, and N. Galin. "Exploring the Benefits of Using CryoSat-2's Cross-Track Interferometry to Improve the Resolution of Multisatellite Mesoscale Fields." Journal of Atmospheric and Oceanic Technology 30, no. 7 (July 1, 2013): 1511–26. http://dx.doi.org/10.1175/jtech-d-12-00156.1.
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Abstract Sea surface height (SSH) measurements provided by pulse-limited radar altimeters are one-dimensional profiles along the satellite's nadir track, with no information whatsoever in the cross-track direction. The anisotropy of resulting SSH profiles is the most limiting factor of mesoscale SSH maps that merge the 1D profiles. This paper explores the potential of the cross-track slope derived from the Cryosphere Satellite-2 (CryoSat-2)'s synthetic aperture radar interferometry (SARin) mode to increase the resolution of mesoscale fields in the cross-track direction. Through idealized 1D simulations, this study shows that it is possible to exploit the dual SARin measurement (cross-track slope and SSH profile) in order to constrain mesoscale mapping in the cross-track direction. An error-free SSH slope allows a single SARin instrument to recover almost as much SSH variance as two coordinated altimeters. Noise-corrupted slopes can also be exploited to improve the mapping, and a breakthrough is observed for SARin errors ranging from 1 to 5 μrad for 150-km-radius features in strong currents, and 0.1–0.5 μrad for global mesoscale. Although only limited experiments might be possible with the error level of current CryoSat-2 data, this paper shows the potential of the SAR interferometry technology to reduce the anisotropy of altimeter measurements if the SARin error is significantly reduced in the future, and in particular in the context of a prospective SARin demonstrator optimized for oceanography.
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Parrish, Christopher E., Lori A. Magruder, Amy L. Neuenschwander, Nicholas Forfinski-Sarkozi, Michael Alonzo, and Michael Jasinski. "Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS’s Bathymetric Mapping Performance." Remote Sensing 11, no. 14 (July 10, 2019): 1634. http://dx.doi.org/10.3390/rs11141634.
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NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) Kd(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and Kd(490) in the range of 0.05–0.12 m−1. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.
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Lendzioch, T., J. Langhammer, and M. Jenicek. "TRACKING FOREST AND OPEN AREA EFFECTS ON SNOW ACCUMULATION BY UNMANNED AERIAL VEHICLE PHOTOGRAMMETRY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 917–23. http://dx.doi.org/10.5194/isprsarchives-xli-b1-917-2016.
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Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV) platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas) and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1) developing a high resolution Digital Elevation Model during snow-free and 2) during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI) retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this method presents the potential of simplifying LAI retrieval and mapping of snow dynamics while reducing running costs and time.
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Lendzioch, T., J. Langhammer, and M. Jenicek. "TRACKING FOREST AND OPEN AREA EFFECTS ON SNOW ACCUMULATION BY UNMANNED AERIAL VEHICLE PHOTOGRAMMETRY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 917–23. http://dx.doi.org/10.5194/isprs-archives-xli-b1-917-2016.
Full textAbstract:
Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV) platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas) and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1) developing a high resolution Digital Elevation Model during snow-free and 2) during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI) retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this method presents the potential of simplifying LAI retrieval and mapping of snow dynamics while reducing running costs and time.
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Young, Duncan A., Laura E. Lindzey, Donald D. Blankenship, Jamin S. Greenbaum, Alvaro Garcia De Gorordo, Scott D. Kempf, Jason L. Roberts, et al. "Land-ice elevation changes from photon-counting swath altimetry: first applications over the Antarctic ice sheet." Journal of Glaciology 61, no. 225 (2015): 17–28. http://dx.doi.org/10.3189/2015jog14j048.
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AbstractSatellite altimetric time series allow high-precision monitoring of ice-sheet mass balance. Understanding elevation changes in these regions is important because outlet glaciers along ice-sheet margins are critical in controlling flow of inland ice. Here we discuss a new airborne altimetry dataset collected as part of the ICECAP (International Collaborative Exploration of the Cryosphere by Airborne Profiling) project over East Antarctica. Using the ALAMO (Airborne Laser Altimeter with Mapping Optics) system of a scanning photon-counting lidar combined with a laser altimeter, we extend the 2003–09 surface elevation record of NASA’s ICESat satellite, by determining cross-track slope and thus independently correcting for ICESat’s cross-track pointing errors. In areas of high slope, cross-track errors result in measured elevation change that combines surface slope and the actual Δz/Δt signal. Slope corrections are particularly important in coastal ice streams, which often exhibit both rapidly changing elevations and high surface slopes. As a test case (assuming that surface slopes do not change significantly) we observe a lack of ice dynamic change at Cook Ice Shelf, while significant thinning occurred at Totten and Denman Glaciers during 2003–09.
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Westermann, S., T. I. Østby, K. Gisnås, T. V. Schuler, and B. Etzelmüller. "A ground temperature map of the North Atlantic permafrost region based on remote sensing and reanalysis data." Cryosphere 9, no. 3 (June 23, 2015): 1303–19. http://dx.doi.org/10.5194/tc-9-1303-2015.
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Abstract. Permafrost is a key element of the terrestrial cryosphere which makes mapping and monitoring of its state variables an imperative task. We present a modeling scheme based on remotely sensed land surface temperatures and reanalysis products from which mean annual ground temperatures (MAGT) can be derived at a spatial resolution of 1 km at continental scales. The approach explicitly accounts for the uncertainty due to unknown input parameters and their spatial variability at subgrid scale by delivering a range of MAGTs for each grid cell. This is achieved by a simple equilibrium model with only few input parameters which for each grid cell allows scanning the range of possible results by running many realizations with different parameters. The approach is applied to the unglacierized land areas in the North Atlantic region, an area of more than 5 million km2 ranging from the Ural Mountains in the east to the Canadian Archipelago in the west. A comparison to in situ temperature measurements in 143 boreholes suggests a model accuracy better than 2.5 °C, with 139 considered boreholes within this margin. The statistical approach with a large number of realizations facilitates estimating the probability of permafrost occurrence within a grid cell so that each grid cell can be classified as continuous, discontinuous and sporadic permafrost. At its southern margin in Scandinavia and Russia, the transition zone between permafrost and permafrost-free areas extends over several hundred km width with gradually decreasing permafrost probabilities. The study exemplifies the unexploited potential of remotely sensed data sets in permafrost mapping if they are employed in multi-sensor multi-source data fusion approaches.
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Westermann, S., T. Østby, K. Gisnås, T. V. Schuler, and B. Etzelmüller. "A ground temperature map of the North Atlantic permafrost region based on remote sensing and reanalysis data." Cryosphere Discussions 9, no. 1 (February 2, 2015): 753–90. http://dx.doi.org/10.5194/tcd-9-753-2015.
Full textAbstract:
Abstract. Permafrost is a key element of the terrestrial cryosphere which makes mapping and monitoring of its state variables an imperative task. We present a modeling scheme based on remotely sensed land surface temperatures and reanalysis products from which mean annual ground temperatures (MAGT) can be derived at a spatial resolution of 1 km on continental scale. The approach explicitly accounts for the uncertainty due to unknown input parameters and their spatial variability at subgrid scale by delivering a range of MAGTs for each grid cell. This is achieved by a simple equilibrium model with only few input parameters which for each grid cell allows scanning the range of possible results by running many realizations with different parameters. The approach is applied to the unglacierized land areas in the North Atlantic region, an area of more than 5 million km2 ranging from the Ural mountains in the East to the Canadian Archipelago in the West. A comparison to in-situ temperature measurements in 143 boreholes suggests a model accuracy better than 2.5 °C, with 139 considered boreholes within this margin. The statistical approach with a large number of realizations facilitates estimating the probability of permafrost occurrence within a grid cell so that each grid cell can be classified as continuous, discontinuous and sporadic permafrost. At its southern margin in Scandinavia and Russia, the transition zone between permafrost and permafrost-free areas extends over several hundred km width with gradually decreasing permafrost probabilities. The study exemplifies the unexploited potential of remotely sensed data sets in permafrost mapping if they are employed in multi-sensor multi-source data fusion approaches.
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Scher, Corey, Nicholas C. Steiner, and Kyle C. McDonald. "Mapping seasonal glacier melt across the Hindu Kush Himalaya with time series synthetic aperture radar (SAR)." Cryosphere 15, no. 9 (September 24, 2021): 4465–82. http://dx.doi.org/10.5194/tc-15-4465-2021.
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Abstract. Current observational data on Hindu Kush Himalayas (HKH) glaciers are sparse, and characterizations of seasonal melt dynamics are limited. Time series synthetic aperture radar (SAR) imagery enables detection of reach-scale glacier melt characteristics across continents. We analyze C-band Sentinel-1 A/B SAR time series data, comprised of 32 741 Sentinel-1 A/B SAR images, and determine the duration of seasonal glacier melting for 105 432 mapped glaciers (83 102 km2 glacierized area, defined using optical observations) in the HKH across the calendar years 2017–2019. Melt onset and duration are recorded at 90 m spatial resolution and 12 d temporal repeat. All glacier areas within the HKH exhibit some degree of melt. Melt signals persist for over two-thirds of the year at elevations below 4000 m a.s.l. and for nearly half of the calendar year at elevations exceeding 7000 m a.s.l. Retrievals of seasonal melting span all elevation ranges of glacierized area in the HKH region, extending greater than 1 km above the maximum elevation of an interpolated 0 ∘C summer isotherm and at the top of Mount Everest, where in situ data and surface energy balance models indicate that the Khumbu Glacier is melting at surface air temperatures below −10 ∘C. Sentinel-1 melt retrievals reflect broad-scale trends in glacier mass balance across the region, where the duration of melt retrieved in the Karakoram is on average 16 d less than in the eastern Himalaya sub-region. Furthermore, percolation zones are apparent from meltwater retention indicated by delayed refreeze. Time series SAR datasets are suitable to support operational monitoring of glacier surface melt and the development and assessment of surface energy balance models of melt-driven ablation across the global cryosphere.
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Buckel, Johannes, Eike Reinosch, Andreas Hördt, Fan Zhang, Björn Riedel, Markus Gerke, Antje Schwalb, and Roland Mäusbacher. "Insights into a remote cryosphere: a multi-method approach to assess permafrost occurrence at the Qugaqie basin, western Nyainqêntanglha Range, Tibetan Plateau." Cryosphere 15, no. 1 (January 11, 2021): 149–68. http://dx.doi.org/10.5194/tc-15-149-2021.
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Abstract. Permafrost as a climate-sensitive parameter and its occurrence and distribution play an important role in the observation of global warming. However, field-based permafrost distribution data and information on the subsurface ice content in the large area of the southern mountainous Tibetan Plateau (TP) are very sparse. Existing models based on boreholes and remote sensing approaches suggest permafrost probabilities for most of the Tibetan mountain ranges. Field data to validate permafrost models are generally lacking because access to the mountain regions in extreme altitudes is limited. The study provides geomorphological and geophysical field data from a north-orientated high-altitude catchment in the western Nyainqêntanglha Range. A multi-method approach combines (A) geomorphological mapping, (B) electrical resistivity tomography (ERT) to identify subsurface ice occurrence and (C) interferometric synthetic aperture radar (InSAR) analysis to derive multi-annual creeping rates. The combination of the resulting data allows an assessment of the lower occurrence of permafrost in a range of 5350 and 5500 m above sea level (a.s.l.) in the Qugaqie basin. Periglacial landforms such as rock glaciers and protalus ramparts are located in the periglacial zone from 5300–5600 m a.s.l. The altitudinal periglacial landform distribution is supported by ERT data detecting ice-rich permafrost in a rock glacier at 5500 m a.s.l. and ice lenses around the rock glacier (5450 m a.s.l.). The highest multiannual creeping rates up to 150 mm yr−1 are typically observed on these rock glaciers. This study closes the gap of unknown state of periglacial features and potential permafrost occurrence in a high-elevated basin in the western Nyainqêntanglha Range (Tibetan Plateau).
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Buckel, Johannes, Eike Reinosch, Andreas Hördt, Fan Zhang, Björn Riedel, Markus Gerke, Antje Schwalb, and Roland Mäusbacher. "Insights into a remote cryosphere: a multi-method approach to assess permafrost occurrence at the Qugaqie basin, western Nyainqêntanglha Range, Tibetan Plateau." Cryosphere 15, no. 1 (January 11, 2021): 149–68. http://dx.doi.org/10.5194/tc-15-149-2021.
Full textAbstract:
Abstract. Permafrost as a climate-sensitive parameter and its occurrence and distribution play an important role in the observation of global warming. However, field-based permafrost distribution data and information on the subsurface ice content in the large area of the southern mountainous Tibetan Plateau (TP) are very sparse. Existing models based on boreholes and remote sensing approaches suggest permafrost probabilities for most of the Tibetan mountain ranges. Field data to validate permafrost models are generally lacking because access to the mountain regions in extreme altitudes is limited. The study provides geomorphological and geophysical field data from a north-orientated high-altitude catchment in the western Nyainqêntanglha Range. A multi-method approach combines (A) geomorphological mapping, (B) electrical resistivity tomography (ERT) to identify subsurface ice occurrence and (C) interferometric synthetic aperture radar (InSAR) analysis to derive multi-annual creeping rates. The combination of the resulting data allows an assessment of the lower occurrence of permafrost in a range of 5350 and 5500 m above sea level (a.s.l.) in the Qugaqie basin. Periglacial landforms such as rock glaciers and protalus ramparts are located in the periglacial zone from 5300–5600 m a.s.l. The altitudinal periglacial landform distribution is supported by ERT data detecting ice-rich permafrost in a rock glacier at 5500 m a.s.l. and ice lenses around the rock glacier (5450 m a.s.l.). The highest multiannual creeping rates up to 150 mm yr−1 are typically observed on these rock glaciers. This study closes the gap of unknown state of periglacial features and potential permafrost occurrence in a high-elevated basin in the western Nyainqêntanglha Range (Tibetan Plateau).
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O'Regan, Matt, Jan Backman, Natalia Barrientos, Thomas M. Cronin, Laura Gemery, Nina Kirchner, Larry A. Mayer, et al. "The De Long Trough: a newly discovered glacial trough on the East Siberian continental margin." Climate of the Past 13, no. 9 (September 28, 2017): 1269–84. http://dx.doi.org/10.5194/cp-13-1269-2017.
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Abstract. Ice sheets extending over parts of the East Siberian continental shelf have been proposed for the last glacial period and during the larger Pleistocene glaciations. The sparse data available over this sector of the Arctic Ocean have left the timing, extent and even existence of these ice sheets largely unresolved. Here we present new geophysical mapping and sediment coring data from the East Siberian shelf and slope collected during the 2014 SWERUS-C3 expedition (SWERUS-C3: Swedish – Russian – US Arctic Ocean Investigation of Climate-Cryosphere-Carbon Interactions). The multibeam bathymetry and chirp sub-bottom profiles reveal a set of glacial landforms that include grounding zone formations along the outer continental shelf, seaward of which lies a > 65 m thick sequence of glacio-genic debris flows. The glacial landforms are interpreted to lie at the seaward end of a glacial trough – the first to be reported on the East Siberian margin, here referred to as the De Long Trough because of its location due north of the De Long Islands. Stratigraphy and dating of sediment cores show that a drape of acoustically laminated sediments covering the glacial deposits is older than ∼ 50 cal kyr BP. This provides direct evidence for extensive glacial activity on the Siberian shelf that predates the Last Glacial Maximum and most likely occurred during the Saalian (Marine Isotope Stage (MIS) 6).
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Zhang, Meimei, Fang Chen, Bangsen Tian, Dong Liang, and Aqiang Yang. "High-Frequency Glacial Lake Mapping Using Time Series of Sentinel-1A/1B SAR Imagery: An Assessment for the Southeastern Tibetan Plateau." International Journal of Environmental Research and Public Health 17, no. 3 (February 8, 2020): 1072. http://dx.doi.org/10.3390/ijerph17031072.
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Glacial lakes are an important component of the cryosphere in the Tibetan Plateau. In response to climate warming, they threaten the downstream lives, ecological environment, and public infrastructures through outburst floods within a short time. Although most of the efforts have been made toward extracting glacial lake outlines and detect their changes with remotely sensed images, the temporal frequency and spatial resolution of glacial lake datasets are generally not fine enough to reflect the detailed processes of glacial lake dynamics, especially for potentially dangerous glacial lakes with high-frequency variability. By using full time-series Sentinel-1A/1B imagery over a year, this study presents a new systematic method to extract the glacial lake outlines that have a fast variability in the southeastern Tibetan Plateau with a time interval of six days. Our approach was based on a level-set segmentation, combined with a median pixel composition of synthetic aperture radar (SAR) backscattering coefficients stacked as a regularization term, to robustly estimate the lake extent across the observed time range. The mapping results were validated against manually digitized lake outlines derived from Gaofen-2 panchromatic multi-spectral (GF-2 PMS) imagery, with an overall accuracy and kappa coefficient of 96.54% and 0.95, respectively. In comparison with results from classical supervised support vector machine (SVM) and unsupervised Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA) methods, the proposed method proved to be much more robust and effective at detecting glacial lakes with irregular boundaries that have similar backscattering as the surroundings. This study also demonstrated the feasibility of time-series Sentinel-1A/1B SAR data in the continuous monitoring of glacial lake outline dynamics.
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Carmack, E., I. Polyakov, L. Padman, I. Fer, E. Hunke, J. Hutchings, J. Jackson, et al. "Toward Quantifying the Increasing Role of Oceanic Heat in Sea Ice Loss in the New Arctic." Bulletin of the American Meteorological Society 96, no. 12 (December 1, 2015): 2079–105. http://dx.doi.org/10.1175/bams-d-13-00177.1.
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Abstract The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions.
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Jiang, J., A. Shaker, and H. Zhang. "PREFACE: TECHNICAL COMMISSION III." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 7. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-7-2021.
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Abstract. The work of ISPRS Technical Commission III is devoted to remote sensing. For the XXIVth ISPRS CONGRESS – 2021 Edition (Digital), Technical Commission III received total 201 submissions, including 72 full papers and 138 abstracts. Among these submissions 38 are accepted as peer-reviewed contributions for publication in the ISPRS Annals, 118 were accepted for publication in the ISPRS Archives.These papers are dedicated mostly to topics of the 10 TC III working groups and 4 inter-commission working groups as follows – WG III/1: Thematic Information Extraction; WG III/2: Microwave Remote Sensing; WG III/3: SAR-based Surface Generation and Deformation Monitoring; WG III/4: Hyperspectral Image Processing; WG III/5: Information Extraction from LiDAR Intensity Data; WG III/6: Remote Sensing Data Fusion; WG III/7: Landuse and Landcover Change Detection; WG III/8: Remote Sensing of Atmospheric Environment; WG III/9: Cryosphere and Hydrosphere; WG III/10: Agriculture and Natural Ecosystems Modelling and Monitoring; ICWG III/II: Planetary Remote Sensing and Mapping; ICWG III/Iva: Disaster Assessment, Monitoring and Management; ICWG III/IVb: Remote Sensing Data Quality; ICWG III/IVc: Environment and Health. The papers and abstracts were evaluated by the experts in the field and Working Group Chairs according to content, significance, originality, relevance, and clearness of presentation.We would like to thank the authors for their contributions, the reviewers for their reviewing, the working group officers for their efforts on calling for papers, and the organizers of the Congress for publishing this volume.
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Jiang, J., A. Shaker, and H. Zhang. "PREFACE: TECHNICAL COMMISSION III." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021 (June 17, 2021): 7. http://dx.doi.org/10.5194/isprs-annals-v-3-2021-7-2021.
Full textAbstract:
Abstract. The work of ISPRS Technical Commission III is devoted to remote sensing. For the XXIVth ISPRS CONGRESS – 2021 Edition (Digital), Technical Commission III received total 201 submissions, including 72 full papers and 138 abstracts. Among these submissions 38 are accepted as peer-reviewed contributions for publication in the ISPRS Annals, 118 were accepted for publication in the ISPRS Archives.These papers are dedicated mostly to topics of the 10 TC III working groups and 4 inter-commission working groups as follows – WG III/1: Thematic Information Extraction; WG III/2: Microwave Remote Sensing; WG III/3: SAR-based Surface Generation and Deformation Monitoring; WG III/4: Hyperspectral Image Processing; WG III/5: Information Extraction from LiDAR Intensity Data; WG III/6: Remote Sensing Data Fusion; WG III/7: Landuse and Landcover Change Detection; WG III/8: Remote Sensing of Atmospheric Environment; WG III/9: Cryosphere and Hydrosphere; WG III/10: Agriculture and Natural Ecosystems Modelling and Monitoring; ICWG III/II: Planetary Remote Sensing and Mapping; ICWG III/Iva: Disaster Assessment, Monitoring and Management; ICWG III/IVb: Remote Sensing Data Quality; ICWG III/IVc: Environment and Health. The papers and abstracts were evaluated by the experts in the field and Working Group Chairs according to content, significance, originality, relevance, and clearness of presentation.We would like to thank the authors for their contributions, the reviewers for their reviewing, the working group officers for their efforts on calling for papers, and the organizers of the Congress for publishing this volume.
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Wu, Renzhe, Guoxiang Liu, Rui Zhang, Xiaowen Wang, Yong Li, Bo Zhang, Jialun Cai, and Wei Xiang. "A Deep Learning Method for Mapping Glacial Lakes from the Combined Use of Synthetic-Aperture Radar and Optical Satellite Images." Remote Sensing 12, no. 24 (December 8, 2020): 4020. http://dx.doi.org/10.3390/rs12244020.
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Glacial lakes (GLs), a vital link between the hydrosphere and the cryosphere, participate in the local hydrological process, and their interannual dynamic evolution is an objective reflection and an indicator of regional climate change. The complex terrain and climatic conditions in mountainous areas where GLs are located make it difficult to employ conventional remote sensing observation means to obtain stable, accurate, and comprehensive observation data. In view of this situation, this study presents an algorithm with a high generalization ability established by optimizing and improving a deep learning (DL) semantic segmentation network model for extracting GL contours from combined synthetic-aperture radar (SAR) amplitude and multispectral imagery data. The aim is to use the high penetrability and all-weather advantages of SAR to reduce the effects of cloud cover as well as to integrate the multiscale and detail-oriented advantages of multispectral data to facilitate accurate, quantitative extraction of GL contours. The accuracy and reliability of the model and algorithm were examined by employing them to extract the contours of GLs in a large region of south-eastern Tibet from Landsat 8 optical remote sensing images and Sentinel-1A amplitude images. In this study, the contours of a total 8262 GLs in south-eastern Tibet were extracted. These GLs were distributed predominantly at altitudes of 4000–5500 m. Only 17.4% of these GLs were greater than 0.1 km2 in size, while a large number of small GLs made up the majority. Through analysis and validation, the proposed method was found highly capable of distinguishing rivers and lakes and able to effectively reduce the misidentification and extraction of rivers. With the DL model based on combined optical and SAR images, the intersection-over-union (IoU) score increased by 0.0212 (to 0.6207) on the validation set and by 0.038 (to 0.6397) on the prediction set. These validation data sufficiently demonstrate the efficacy of the model and algorithm. The technical means employed in this study as well as the results and data obtained can provide a reference for research and application expansion in related fields.
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Zhang, Y., I. Olthof, R. Fraser, and S. A. Wolfe. "Corrigendum to "A new approach to mapping permafrost and change incorporating uncertainties in ground conditions and climate projections" published in The Cryosphere, 8, 2177–2194, 2014." Cryosphere 8, no. 6 (December 3, 2014): 2253. http://dx.doi.org/10.5194/tc-8-2253-2014.
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Jiang, J., A. Shaker, and H. Zhang. "PREFACE: TECHNICAL COMMISSION III." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 7–8. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-7-2020.
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Abstract. The work of ISPRS Technical Commission III is devoted to remote sensing. For the XXIVth ISPRS CONGRESS, Technical Commission III received total 603 submissions 216 full papers and 387 abstracts. Among these submissions 107 are accepted as peer-reviewed contributions for publication in the ISPRS Annals, 218 were accepted for publication in the ISPRS Archives. There are 228 accepted submissions were withdrawn by authors due to the postpone of the Congress and other reasons.These papers are dedicated mostly to topics of the 10 TC III working groups and 4 inter-commission working groups as follows – WG III/1: Thematic Information Extraction; WG III/2: Microwave Remote Sensing; WG III/3: SAR-based Surface Generation and Deformation Monitoring; WG III/4: Hyperspectral Image Processing; WG III/5: Information Extraction from LiDAR Intensity Data; WG III/6: Remote Sensing Data Fusion; WG III/7: Landuse and Landcover Change Detection; WG III/8: Remote Sensing of Atmospheric Environment; WG III/9: Cryosphere and Hydrosphere; WG III/10: Agriculture and Natural Ecosystems Modelling and Monitoring; ICWG III/II: Planetary Remote Sensing and Mapping; ICWG III/Iva: Disaster Assessment, Monitoring and Management; ICWG III/IVb: Remote Sensing Data Quality; ICWG III/IVc: Environment and Health. The papers and abstracts were evaluated by the experts in the field and Working Group Chairs according to content, significance, originality, relevance, and clearness of presentation.We would like to thank the authors for their contributions, the reviewers for their reviewing, the working group officers for their efforts on calling for papers, and the organizers of the Congress for publishing this volume.
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Jiang, J., A. Shaker, and H. Zhang. "PREFACE: TECHNICAL COMMISSION III." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 7–8. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-7-2020.
Full textAbstract:
Abstract. The work of ISPRS Technical Commission III is devoted to remote sensing. For the XXIVth ISPRS CONGRESS, Technical Commission III received total 603 submissions 216 full papers and 387 abstracts. Among these submissions 107 are accepted as peer-reviewed contributions for publication in the ISPRS Annals, 218 were accepted for publication in the ISPRS Archives. There are 228 accepted submissions were withdrawn by authors due to the postpone of the Congress and other reasons.These papers are dedicated mostly to topics of the 10 TC III working groups and 4 inter-commission working groups as follows – WG III/1: Thematic Information Extraction; WG III/2: Microwave Remote Sensing; WG III/3: SAR-based Surface Generation and Deformation Monitoring; WG III/4: Hyperspectral Image Processing; WG III/5: Information Extraction from LiDAR Intensity Data; WG III/6: Remote Sensing Data Fusion; WG III/7: Landuse and Landcover Change Detection; WG III/8: Remote Sensing of Atmospheric Environment; WG III/9: Cryosphere and Hydrosphere; WG III/10: Agriculture and Natural Ecosystems Modelling and Monitoring; ICWG III/II: Planetary Remote Sensing and Mapping; ICWG III/Iva: Disaster Assessment, Monitoring and Management; ICWG III/IVb: Remote Sensing Data Quality; ICWG III/IVc: Environment and Health. The papers and abstracts were evaluated by the experts in the field and Working Group Chairs according to content, significance, originality, relevance, and clearness of presentation.We would like to thank the authors for their contributions, the reviewers for their reviewing, the working group officers for their efforts on calling for papers, and the organizers of the Congress for publishing this volume.
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Opie, Simon, Richard G. Taylor, Chris M. Brierley, Mohammad Shamsudduha, and Mark O. Cuthbert. "Climate–groundwater dynamics inferred from GRACE and the role of hydraulic memory." Earth System Dynamics 11, no. 3 (August 27, 2020): 775–91. http://dx.doi.org/10.5194/esd-11-775-2020.
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Abstract. Groundwater is the largest store of freshwater on Earth after the cryosphere and provides a substantial proportion of the water used for domestic, irrigation and industrial purposes. Knowledge of this essential resource remains incomplete, in part, because of observational challenges of scale and accessibility. Here we examine a 14-year period (2002–2016) of Gravity Recovery and Climate Experiment (GRACE) observations to investigate climate–groundwater dynamics of 14 tropical and sub-tropical aquifers selected from WHYMAP's (Worldwide Hydrogeological Mapping and Assessment Programme) 37 large aquifer systems of the world. GRACE-derived changes in groundwater storage resolved using GRACE Jet Propulsion Laboratory (JPL) mascons and the Community Land Model's land surface model are related to precipitation time series and regional-scale hydrogeology. We show that aquifers in dryland environments exhibit long-term hydraulic memory through a strong correlation between groundwater storage changes and annual precipitation anomalies integrated over the time series; aquifers in humid environments show short-term memory through strong correlation with monthly precipitation. This classification is consistent with estimates of groundwater response times calculated from the hydrogeological properties of each system, with long (short) hydraulic memory associated with slow (rapid) response times. The results suggest that groundwater systems in dryland environments may be less sensitive to seasonal climate variability but vulnerable to long-term trends from which they will be slow to recover. In contrast, aquifers in humid regions may be more sensitive to climate disturbances such as drought related to the El Niño–Southern Oscillation but may also be relatively quick to recover. Exceptions to this general pattern are traced to human interventions through groundwater abstraction. Hydraulic memory is an important factor in the management of groundwater resources, particularly under climate change.
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Zhang, Guoqing, Youhua Ran, Wei Wan, Wei Luo, Wenfeng Chen, Fenglin Xu, and Xin Li. "100 years of lake evolution over the Qinghai–Tibet Plateau." Earth System Science Data 13, no. 8 (August 13, 2021): 3951–66. http://dx.doi.org/10.5194/essd-13-3951-2021.
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Abstract. Lakes can be effective indicators of climate change, and this is especially so for the lakes over the Qinghai–Tibet Plateau (QTP), the highest plateau in the world, which undergoes little direct human influence. The QTP has warmed at twice the mean global rate, and the lakes there respond rapidly to climate and cryosphere changes. The QTP has ∼ 1200 lakes larger than 1 km2 with a total area of ∼ 46 000 km2, accounting for approximately half the number and area of lakes in China. The lakes over the QTP have been selected as an essential example for global lakes or water body studies. However, concerning lake data over the QTP are limited to the Landsat era and/or available at sparse intervals. Here, we extend the record to provide comprehensive lake evolution data sets covering the past 100 years (from 1920 to 2020). Lake mapping in 1920 was derived from an early map of the Republic of China and in 1960 from the topographic map of China. The densest lake inventories produced so far between 1970 and 2020 (covering all lakes larger than 1 km2 in 14 epochs) are mapped from Landsat MSS, TM, ETM+, and OLI images. The lake evolution shows remarkable transitions between four phases: significant shrinkage in 1920–1995, rapid linear increase in 1995–2010, relative stability in 2010–2015, and further increase in 2015–2020. The spatial pattern indicates that the majority of lakes shrank in 1920–1995 and expanded in 1995–2020, with a dominant enlargement for central-north lakes in contrast to contraction for southern lakes in 1976–2020. The time series of precipitation between 1920 and 2017 indirectly supports the evolution trends of lakes identified in this study. The lake data set is freely available at https://doi.org/10.5281/zenodo.4678104 (Zhang et al., 2021a).
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Cao, Changyong, Bin Zhang, Xi Shao, Wenhui Wang, Sirish Uprety, Taeyoung Choi, Slawomir Blonski, et al. "Mission-Long Recalibrated Science Quality Suomi NPP VIIRS Radiometric Dataset Using Advanced Algorithms for Time Series Studies." Remote Sensing 13, no. 6 (March 12, 2021): 1075. http://dx.doi.org/10.3390/rs13061075.
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Suomi NPP has been successfully operating since its launch on 28 October 2011. As one of the major payloads, along with microwave and infrared sounders (Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS)), and ozone mapping/profiling (OMPS) instruments, the Visible Infrared Imaging Radiometer Suite (VIIRS) has performed for well beyond its mission design life. Its data have been used for a variety of applications for nearly 30 environmental data products, including global imagery twice daily with 375 and 750 m resolutions, clouds, aerosol, cryosphere, ocean color and sea-surface temperature, a number of land products (vegetation, land-cover, fire and others), and geophysical and social economic studies with nightlights. During the early days of VIIRS operational calibration and data production, there were inconsistencies in both algorithms and calibration inputs, for several reasons. While these inconsistencies have less impact on nowcasting and near real-time applications, they introduce challenges for time series analysis due to calibration artifacts. To address this issue, we developed a comprehensive algorithm, and recalibrated and reprocessed the Suomi NPP VIIRS radiometric data that have been produced since the launch. In the recalibration, we resolved inconsistencies in the processing algorithms, terrain correction, straylight correction, and anomalies in the thermal bands. To improve the stability of the reflective solar bands, we developed a Kalman filtering model to incorporate onboard solar, lunar, desert site, inter-satellite calibration, and a deep convective cloud calibration methodology. We further developed and implemented the Solar Diffuser Surface Roughness Rayleigh Scattering model to account for the sensor responsivity degradation in the near infrared bands. The recalibrated dataset was validated using vicarious sites and alternative methods, and compared with independent processing from other organizations. The recalibrated radiometric dataset (namely, the level 1b or sensor data records) also incorporates a bias correction for the reflective solar bands, which not only addresses known calibration biases, but also allows alternative calibrations to be applied if so desired. The recalibrated data have been proven to be of high quality, with much improved stability (better than 0.3%) and accuracy (by up to 2%). The recalibrated radiance data are now available from 2012 to 2020 for users and will eventually be archived on the NOAA CLASS database.
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Westermann, Sebastian, Maria Peter, Moritz Langer, Georg Schwamborn, Lutz Schirrmeister, Bernd Etzelmüller, and Julia Boike. "Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia." Cryosphere 11, no. 3 (June 28, 2017): 1441–63. http://dx.doi.org/10.5194/tc-11-1441-2017.
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Abstract. Permafrost is a sensitive element of the cryosphere, but operational monitoring of the ground thermal conditions on large spatial scales is still lacking. Here, we demonstrate a remote-sensing-based scheme that is capable of estimating the transient evolution of ground temperatures and active layer thickness by means of the ground thermal model CryoGrid 2. The scheme is applied to an area of approximately 16 000 km2 in the Lena River delta (LRD) in NE Siberia for a period of 14 years. The forcing data sets at 1 km spatial and weekly temporal resolution are synthesized from satellite products and fields of meteorological variables from the ERA-Interim reanalysis. To assign spatially distributed ground thermal properties, a stratigraphic classification based on geomorphological observations and mapping is constructed, which accounts for the large-scale patterns of sediment types, ground ice and surface properties in the Lena River delta. A comparison of the model forcing to in situ measurements on Samoylov Island in the southern part of the study area yields an acceptable agreement for the purpose of ground thermal modeling, for surface temperature, snow depth, and timing of the onset and termination of the winter snow cover. The model results are compared to observations of ground temperatures and thaw depths at nine sites in the Lena River delta, suggesting that thaw depths are in most cases reproduced to within 0.1 m or less and multi-year averages of ground temperatures within 1–2 °C. Comparison of monthly average temperatures at depths of 2–3 m in five boreholes yielded an RMSE of 1.1 °C and a bias of −0.9 °C for the model results. The highest ground temperatures are calculated for grid cells close to the main river channels in the south as well as areas with sandy sediments and low organic and ice contents in the central delta, where also the largest thaw depths occur. On the other hand, the lowest temperatures are modeled for the eastern part, which is an area with low surface temperatures and snow depths. The lowest thaw depths are modeled for Yedoma permafrost featuring very high ground ice and soil organic contents in the southern parts of the delta. The comparison to in situ observations indicates that transient ground temperature modeling forced by remote-sensing data is generally capable of estimating the thermal state of permafrost (TSP) and its time evolution in the Lena River delta. The approach could hence be a first step towards remote detection of ground thermal conditions and active layer thickness in permafrost areas.
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Zou, Cheng-Zhi, Lihang Zhou, Lin Lin, Ninghai Sun, Yong Chen, Lawrence E. Flynn, Bin Zhang, et al. "The Reprocessed Suomi NPP Satellite Observations." Remote Sensing 12, no. 18 (September 6, 2020): 2891. http://dx.doi.org/10.3390/rs12182891.
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The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.
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Anderson, Justin, John Holbrook, and Ronald J. Goble. "The ups and downs of the Missouri River from Pleistocene to present: Impact of climatic change and forebulge migration on river profiles, river course, and valley fill complexity." GSA Bulletin, March 29, 2021. http://dx.doi.org/10.1130/b35909.1.
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The Missouri River is a continent-scale river that has thus far escaped a rigorous reporting of valley fill trends within its trunk system. This study summarizes evolution of the lower Missouri River profile from the time of outwash in the Last Glacial Maximum (LGM) until establishment of the modern dominantly precipitation-fed river. This work relies on optically stimulated luminescence (OSL) dating, water-well data, and a collection of surficial geological maps of the valley compiled from U.S. Geological Survey EDMAP and National Science Foundation Research Experience for Undergrads projects. Mapping reveals five traceable surfaces within valley fill between Yankton, South Dakota, USA, and Columbia, Missouri, USA, that record two cycles of incision and aggradation between ca. 23 ka and ca. 8 ka. The river aggraded during the LGM to form the Malta Bend surface by ca. 26 ka. The Malta Bend surface is buried and fragmented but presumed to record a braided outwash plain. The Malta Bend surface was incised up to 18 m between ca. 23 ka and ca. 16 ka to form the Carrolton surface (ca. 16 ka to ca. 14 ka). The Carrollton surface ghosts a braided outwash morphology locally through overlying mud. Aggradation followed (ca. 14 ka to ca. 13.5 ka) to within 4 m of the modern floodplain surface and generated the Salix surface (ca. 13.5 to ca. 12 ka). By Salix time, the Missouri River was no longer an outwash river and formed a single-thread meandering pattern. Reincision at ca. 12 ka followed Salix deposition to form the short-lived Vermillion surface at approximately the grade of the earlier Carrolton surface. Rapid aggradation from ca. 10 ka to ca. 8 ka followed and formed the modern Omaha surface (ca. 8 ka to Present). The higher Malta Bend and Omaha profiles are at roughly the same grade, as are the lower Carrolton and Vermillion surfaces. The Salix surface is in between. All surfaces converge downstream as they enter the narrow and shallow bedrock valley just before reaching Columbia, Missouri. The maximum departure of the profiles is 18 m near Sioux City, Iowa, USA, at ∼100 km downstream from the James Lobe glacial input near Yankton, South Dakota. Incision and aggradation appear to be driven by relative changes in input of sediment and water related to glacial advance and retreat and then later by climatic changes near the Holocene transition. The incision from the Malta Bend to the Carrolton surface records the initial breakdown of the cryosphere at the end of the LGM, and this same incisional event is found in both the Ohio and Mississippi valleys. This incisional event records a “big wash” that resulted in the evacuation of sediment from each of the major outwash rivers of North America. The direction and magnitude of incision from the LGM to the modern does not fit with modeled glacioisostatic adjustment trends for the Missouri Valley. Glaciotectonics likely influenced the magnitude of incision and aggradation secondarily but does not appear to have controlled the overall timing or magnitude of either. Glaciotectonic valley tilting during the Holocene, however, did likely cause the Holocene channel to consistently migrate away from the glacial front, which argues for a forebulge axis south of the Missouri Valley during the Holocene and, by inference, earlier. This is at least 200 km south of where models predict the Holocene forebulge axis. The Missouri Valley thus appears to reside in the tectonic low between the ice front and the forebulge crest. The buffer valley component of incision caused by profile variation could explain as much as 25 m of the total ∼40 m of valley incision at Sioux City, Iowa. The Missouri Valley also hosted a glacial lobe as far south as Sioux City, Iowa, in pre-Wisconsinan time, which is also a factor in valley excavation.